FEWS NET Guidance Document Series

The FEWS NET Guidance Document series focuses on scenario development, the core methodology that FEWS NET uses to make food security projections, and the integration of advanced sectoral concepts and techniques into the scenario development process. Assumptions – about factors such as rainfall, price behavior, conflict, income opportunities, and harvest prospects, among many others – are at the core of the scenario development process. The strength of a scenario depends upon the development of evidence-based and well-informed assumptions about the future. FEWS NET created this series of guidance documents on the most critical assumptions to help food security analysts develop robust scenarios. For an overview of our work, click here.

Food security early warning requires the estimation of future food security outcomes many months in advance, so that decision makers have adequate time to plan for and respond to potential humanitarian crises. However, the complex web of factors shaping food security makes it impossible to definitively predict future outcomes. Scenario development is a methodology that allows FEWS NET to reconcile these two issues by developing a “most likely” scenario of the future. This allows FEWS NET to fulfill its primary mandate to provide early warning on food security crises to decision makers. This paper is the first in a series of guidance documents developed by FEWS NET on integrating advanced sectoral concepts and techniques into the scenario development process.

This guidance document focuses on the process and approach used by FEWS NET to develop assumptions about the performance of rainfall (onset, totals, distribution, cessation) at various points in the year, including before a season begins, once forecasts are available, and throughout the season. Analysts will learn how to understand climatology, evaluate relevant climate modes, interpret forecasts, and use remote sensing imagery in developing assumptions. Guidance is also provided on the main sources of information for ongoing seasonal monitoring, including rainfall data, forecasts, and satellite imagery.

This guidance describes how to develop assumptions about future price trends (price projections) using an integrated approach that incorporates verifiable and credible information about factors that influence prices with expert judgment. Rather than focusing solely on a single indicator or the output from a single mathematical model, analysts will understand how to incorporate contextual information (often qualitative) about the determinants of prices (market fundamentals) into their projections. In doing so, analysts will study key factors that affect supply and demand patterns, along with macro-level factors such as global supply issues and institutional policies and frameworks.

This guidance document focuses on the process and approach used by FEWS NET to integrate acute malnutrition and mortality into scenario development. Analysts will learn how to accurately describe the current nutrition and/or mortality situation, explore potential causes of undernutrition, and make assumptions about the evolution of the nutrition and mortality situation over the course of the scenario period. Guidance is provided on how to contextualize nutrition and mortality data in relation to historical and seasonal trends, and how to explore the forces that could change levels of acute malnutrition and/or mortality.

This guidance provides a general introduction to integrating herd dynamics into the scenario development process. Developing assumptions related to pastoral livelihoods requires a good understanding of how various factors, especially rainfall, affect livestock herd size and production, including births, deaths, sales, and slaughters in the herd. This, in turn, allows analysts to make projections of pastoralists’ access to food and cash income from their herds over time. This document also provides a foundation for understanding the more technical, Excel-based herd dynamics modeling tool of rainfall and herd dynamics changes.